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There is also a fp16 branch which stores the fp16 weights,
which could be used to further minimize the RAM usage:
thon
from transformers import GPTJForCausalLM
import torch
device = "cuda"
model = GPTJForCausalLM.from_pretrained(
"EleutherAI/gpt-j-6B",
revision="float16",
torch_dtype=torch.float16,
).to(device)
The model should fit on 16GB GPU for inference. |